The answer is Replace Values, Fill Down, and Fill Up. These three methods are valid because Power Query provides distinct transforms for handling null values: Replace Values substitutes nulls with a specified default, while Fill Down and Fill Up propagate the nearest non-null value into adjacent null cells, effectively carrying forward or backward existing data within a column. On the Microsoft Power BI Data Analyst PL-300 exam, this question tests your practical understanding of Power Query’s M language interface and its data-cleaning transforms, often appearing in scenarios involving incomplete hierarchical or grouped datasets. A common trap is confusing Remove Rows (which deletes entire rows) with Fill transforms—remember that Fill preserves row structure, whereas Remove Rows discards data. For a quick memory tip, think of “Replace, Fill Down, Fill Up” as the three pillars of null handling: replace with a constant, or fill from above or below.
PL-300 Prepare the data Practice Question
This PL-300 practice question tests your understanding of prepare the data. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which THREE are valid methods to handle null values in Power Query? (Choose three.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use the 'Fill Down' or 'Fill Up' option to propagate non-null values into null cells.
Option A is correct because the 'Fill Down' and 'Fill Up' transforms in Power Query propagate the last non-null value into adjacent null cells within a column. This is a common technique for cleaning data where nulls represent missing values that should inherit the previous or next valid entry, such as in hierarchical or grouped datasets.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
Use the 'Fill Down' or 'Fill Up' option to propagate non-null values into null cells.
Why this is correct
Fill Down/Fill Up replaces nulls with the nearest non-null value.
Related concept
Read the scenario before looking for a memorised answer.
✓
Remove rows that contain null values using the 'Remove Rows' > 'Remove Blank Rows' option.
Why this is correct
This removes entire rows if they are blank.
Related concept
Read the scenario before looking for a memorised answer.
✓
Replace null values with a default value using the 'Replace Values' transform.
Why this is correct
Replace Values can substitute nulls with a chosen value.
Related concept
Read the scenario before looking for a memorised answer.
✗
Merge the table with another table that has no nulls.
Why it's wrong here
Merging does not handle nulls; it may introduce more nulls from the other table.
✗
Change the data type of the column to a non-nullable type.
Why it's wrong here
Changing data type does not remove nulls; it may cause errors.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse 'Remove Blank Rows' (which removes entire rows where all cells are null) with 'Remove Rows' > 'Remove Blank Rows' (which is actually a valid method to remove rows with nulls in any column, as option B states), but the real pitfall is assuming that changing a data type to non-nullable will automatically handle nulls, which Power Query does not support.
Detailed technical explanation
How to think about this question
Under the hood, Power Query's 'Fill Down' uses the Table.FillDown function, which iterates through rows in the order of the table and replaces nulls with the last non-null value in the same column. A subtle behavior is that 'Fill Down' only works on columns with the same data type; if the column contains mixed types, it may fail or produce unexpected results. In real-world scenarios, this is critical for flattening parent-child relationships or filling in missing dates in time-series data.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Prepare the data — This question tests Prepare the data — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use the 'Fill Down' or 'Fill Up' option to propagate non-null values into null cells. — Option A is correct because the 'Fill Down' and 'Fill Up' transforms in Power Query propagate the last non-null value into adjacent null cells within a column. This is a common technique for cleaning data where nulls represent missing values that should inherit the previous or next valid entry, such as in hierarchical or grouped datasets.
What should I do if I get this PL-300 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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